Top 10 Applications of Machine Learning | ML Applications and Examples | Machine Learning

[0:00]Hello everyone, my name is Ankit Varma, and today we are learning the applications of Machine Learning. The first application is virtual personal assistant. Say example, we are having the Alexa, Cortana, Hey Siri, Hello Google. These are the virtual personal assistant. Virtual means there is a computer which is virtually present. Personal means they are helping us personally as a assistant. Means whatever we are asking the computer, they are solving our query. So they use the NLP. NLP is Natural Language Processing. So there is an intelligent agent present in the form of computer, and they are understanding our natural language. Means whatever we are speaking, they are understanding, and based upon that, they are recognizing our speech, and they are doing such actions, just like playing the song or giving us the direction, and so many other tasks. So these are the virtual personal assistant. Next application is traffic prediction. Means predicting the traffic. Today we are having the Google Map. And through the Google Map, we can easily find which is the best route for going from one location to another. They are also telling us that wherever we are having the congestion, or which path is free. So easily we can predict the traffic. The next application is email spam filtering. The meaning is that in the email, we are going to filter those mails which are spam. We can see that in our Yahoo or Gmail, we are having the option of spam. So here, all those mails which are not useful for us, or which are fishy, these mails are automatically sent to the spam. So there all the spam mails are collected. This is the application of machine learning. Next application is online fraud detection. Through the machine learning, we can detect the online fraud. Today there are various fraudulent people, who are going to steal our details of ATM card, debit card, by which they are performing the operation and they deduct the money from our bank account. So these are the fraud, and in this online fraud, this can be detected by the machine learning. Next is stock market trading. With the machine learning, we can easily check where the market is growing. What is the upcoming prediction, where we should invest our funds? So with the help of machine learning, we can do the stock market trading. The next application is automatic language translation. One language can be converted to other language automatically. This is called automatic language translation. Let us suppose that somebody is speaking in English, and from the device on the other side we are having the language converted to the Japanese. So here, English and Japanese, these two persons can communicate very easily, and this is done automatically by the machine learning application. The next application is recommendation engine. The meaning is that we are recommending something. Today, the Netflix, YouTube, Amazon Prime, and so many other OTT platforms are recommending their movies. And based upon that, their videos and movies are promoted, and people are watching that. This is the recommender system. Similarly, Amazon, Flipkart, Myntra are recommending their products using the product recommendation. And based upon that, there are so many people who are purchasing their product. This is all possible because of the machine learning. Next is self-driving car. The drivers are not required in the self-driving car, because they can drive by themselves. There are so many sensors which are placed, these sensors can judge the distance from the other car and they can also judge the road traffic, and based upon the machine learning algorithm, they can decide where they should move and at which speed. So these cars are self-driven. Next application is medical diagnosis. We can easily predict the problem with the patient using the machine learning algorithm. Here we can predict what are the probable cause for the problem, and we can treat the patient very easily. The next application is image recognition. Today with the machine learning, we can recognize the face very easily. We can also match the photo with the sketch. Let us suppose that we are having a sketch of a criminal. We can match with the database using the image recognition. So all these are possible because of machine learning. Next application is speech recognition. Our mobile, tablets, they can recognize our speech. Means whatever we are saying, they are doing certain operation, just like if we are saying to call somebody, they are doing the call. So this is the speech recognition which is possible because of NLP, which is natural language processing. They process the human voice and take the decision accordingly. Next application of machine learning is chatbots. Chatbot meaning is chat is chatting, bot means it is a computer-generated bot. So bot is doing the chat. Today in the modern websites, in the corner we are having a chatbot which helps in solving our query. If we have some query, we can type and these chatbot can answer. So based upon our question, they give us the answer. This is only possible because of the machine learning. Next application is virtual try-on. The meaning is that virtually we can try something. Let us suppose that we want to purchase the specs. Then virtually on our face we can place the specs, and we can check which specs is looking good. Or let us suppose that we want to purchase some jeans, we can virtually try it. So, these are the virtual try-on. So using the machine learning, we can virtually try the things which we want. Next application is social media personalization. Using the machine learning, sentiment analysis is done. The meaning is that here we are checking the customer's choice. The customer is happy or not? Means customer want which thing, so we should produce the same thing. That is the sentiment analysis, means analyzing the sentiment of customer. And based upon that, those things which are liked by the customer, they are promoted on the Instagram, Facebook, Twitter, LinkedIn, so that their social media can be personalized, and they can enjoy all the things which they want. Next application is gamified learning. Nowadays there are various apps available, through which kids can play the game, and they can learn about their concepts. So this is the gamified learning, means learn from the games. So these are the all applications of machine learning. That's all for today. Thank you.